Identifying Job Change Timeframes: Helium vs. ChatGPT

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Hi team, im trying to run a column to identify the time frame where the contact changed there last job, when creating the promt Clay recomended Helium, the results using Helium are accurate but when trying to use a cheaper option like Chatgpt the results are not accurate. is there a reason why ? thanks

2 comments

Channeled
APP
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Helium likely provides more accurate job change tracking results because it's specifically designed for this purpose, while ChatGPT is a general-purpose text generation tool. To improve ChatGPT's accuracy for tracking job changes in Clay: 1. Make sure you're providing clear, structured prompts with specific instructions about the job change detection task. 2. Include relevant context in your system message to help ChatGPT understand what you're looking for. 3. Consider using Clay's dedicated job change tracking feature instead, which is designed to monitor contacts and detect when they move companies. 4. For historical job changes, provide both the "Person LinkedIn URL" and "Company LinkedIn URL" columns to enable proper comparison. 5. Check if you have access to the "Contact Employment Start & End Date" data points, which might provide more precise information for ChatGPT to work with.
Sources: Track Job Changes Data points: Gravatar Url & Username | Clay.com ChatGPT: Generate text with OpenAI/GPT Data points: Last Validation Check | Clay.com
Bruno R.
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Hi Brayan, thanks for your message - what you're describing here is actually fully covered by a native set of signals features we provide out of the box. Here's a quick video showing you how you can set this up: https://www.loom.com/share/b9a950e54691472286a20a79c0bbb073?sid=19e32023-3a12-4568-8179-d543b2187280 I hope this was helpful. If there's anything else I can assist you with, please let me know!